جست‌وجوی استاد و پژوهشگر

• Ecohydrology
• Climate Change
• Vadose Zone Hydrology
• +۲ مورد دیگر

Mark Hausner is an Associate Research Professor at the Desert Research Institute (DRI) within the Division of Hydrologic Sciences and affiliated with the Graduate Program of Hydrologic Sciences . His work integrates field studies with numerical models to analyze heat and mass transfer processes, particularly using heat as a tracer for water movement. Education: Ph.D. in Hydrogeology (University of Nevada, Reno, 2013), M.S. in Hydrologic Sciences (2010), B.S. in Civil and Environmental Engineering (Cornell, 1997) Research focuses on climate change impacts on groundwater-surface water interactions, ecohydrology , and thermal dynamics in arid and polar environments. His work includes modeling aquifer responses in Chile’s Altiplano, assessing wildfire effects on water heating via dissolved black carbon, and studying Devils Hole pupfish habitats. Recent publications highlight applications of distributed temperature sensing (DTS) , groundwater flow modeling, and remote sensing in ecosystems. Collaborations span agencies like the U.S. Army , National Park Service , and DOE . Conference presentations emphasize climate-driven population dynamics and hydrogeologic sensing innovations .

Sundaresh Ramnathمشاهده پروفایل

دانشیار

• Accounting
• Taxation
• Financial Reporting
• +۳ مورد دیگر

Sundaresh Ramnath is an Associate Professor at the University of Miami within the Miami Herbert Business School , specializing in the Accounting department. He holds the role of Academic Director for the Global Executive MBA Program, combining leadership responsibilities with academic expertise. His research focuses on critical accounting policy issues, including Effective tax rate (ETR) disclosure strategies Financial asset and liability measurement standards Revenue recognition frameworks (FASB/IASB convergence) Liquidity risk reporting and regulatory compliance Earnings management detection methods Fiscal calendar impacts on financial reporting While no specific awards or grants are documented in the provided materials, his scholarly contributions appear through publications in leading journals like Contemporary Accounting Research and The Accounting Review . His work demonstrates consistent engagement with regulatory developments and practical financial reporting challenges. As Academic Director of the Global Executive MBA Program, he plays a key role in executive education while maintaining active research and teaching responsibilities in accounting disciplines.

• Inverse Problems
• Numerical Analysis
• Solar Imaging
• +۳ مورد دیگر

Anna Volpara is a Research Fellow at the Department of Mathematics (DIMA) of the University of Genova. Her work focuses on numerical analysis and solar imaging techniques, particularly inverse problems in high-energy solar observations. Primary affiliation: Department of Mathematics - DIMA, University of Genova Academic rank: Research Fellow Her research interests include: Inverse problems in astrophysics Hard X-ray observation techniques Fourier-based image reconstruction Kernel methods for solar imaging Recent publications (2023-2025) demonstrate expertise in computational methods for solar flare analysis, STIX imaging, and multi-scale data processing. No scientific awards were mentioned in the available information.

Behtash Babadiمشاهده پروفایل

دانشیار

• Statistical and Adaptive Signal Processing
• Neural Signal Processing
• Systems Neuroscience
• +۳ مورد دیگر

Behtash Babadi is an Associate Professor in the Department of Electrical & Computer Engineering and a faculty member at the Institute for Systems Research and the Brain and Behavior Institute at the University of Maryland, College Park. He also holds affiliate appointments in the Program in Neuroscience & Cognitive Science and the Applied Mathematics & Statistics program. Education: Ph.D. in Engineering Sciences, Harvard University (2011) M.Sc. in Engineering Sciences, Harvard University (2008) B.Sc. in Electrical Engineering, Sharif University of Technology (2006) Research Interests: Dr. Babadi’s work focuses on statistical and adaptive signal processing frameworks for understanding neural systems. Key areas include: Neural signal processing and systems neuroscience Granger causality and functional connectivity analysis Dynamic modeling of neuronal assemblies Applications to auditory processing and cognitive recovery Scientific Contributions: His recent publications address cortical network dynamics, MEG source analysis, and robust causal inference. Notable methods include Network Localized Granger Causality (NLGC) for direct connectivity estimation and multitaper spectral analysis for neuronal spiking data. Awards: NSF CAREER Award (2016) E. Robert Kent Teaching Award (2019) GSAS Merit Fellowship (Harvard, 2010) Collaborations: Dr. Babadi collaborates with institutions like MIT, Harvard, and Massachusetts General Hospital, and participates in interdisciplinary initiatives such as the Brain and Behavior Initiative (BBI) and NIH BRAIN grants.

Jeffrey Walkerمشاهده پروفایل

پژوهشگر ارشد

• Soil Moisture Remote Sensing
• Microwave Radiometry
• Machine Learning for Environmental Data
• +۳ مورد دیگر

Jeffrey Walker is a Research Fellow in the School of Civil Engineering at the University of New South Wales . His work focuses on soil moisture retrieval using advanced remote sensing technologies, including synthetic aperture radar (SAR), L-band and P-band radiometers, and GNSS-R systems. He integrates machine learning algorithms for spatial downscaling, multi-scale modeling, and time-series analysis to improve hydrological monitoring in agricultural, urban, and infrastructure contexts. Key Research Areas : Soil moisture remote sensing, microwave radiometry, machine learning applications in environmental data, geospatial modeling, sustainable construction, and eco-friendly pavement design. Notable Contributions : Development of LSTM neural networks for pavement moisture prediction, novel downscaling methods using optical trapezoid models, and assimilation frameworks for land surface models. Recent Trends : Emphasis on UAV-based radiometry, multi-frequency sensor fusion, and addressing over-optimism in SAR soil moisture modeling. Applications : Smart rehabilitation of pavements, flood model calibration with crowd-sourced data, and crop yield estimation via satellite imagery fusion.

• Dentistry
• Oral and Maxillofacial Surgery
• Bone Regeneration
• +۳ مورد دیگر

Prof. Mehmet Ali ERDEM is a faculty member at Istanbul University Faculty of Dentistry , currently holding the Professor rank in the Department of Oral and Maxillofacial Surgery . He has been affiliated with Istanbul University since 2000, progressing from Research Assistant (2001-2012) to Associate Professor (2012-2020) before becoming Professor in 2020. Doctorate: Istanbul University Faculty of Dentistry (2006) Postgraduate: Istanbul University Faculty of Dentistry (2000-2006) His research focuses on Oral and Maxillofacial Surgery with specific interests in bone regeneration , dental implant biomechanics , oral pathology , and biomaterial applications . Recent work includes finite element analysis of titanium meshes, temperature control in implant surgery, and novel surgical techniques for oroantral fistulas. Scientific output includes 114 WoS publications and 187 WoS H-index . Current research involves in-vitro studies on titanium surface treatments and biomechanical testing of fixation materials. Secretary General: Turkish Association of Oral and Maxillofacial Surgery Member: Turkish Association of Oral and Maxillofacial Surgery since 2002 Active in scientific conferences across Turkey and international venues like the USA and UK. Supervised 1 thesis and participates in research grants related to bone regeneration and implant stability.

Patrick Guthمشاهده پروفایل

پژوهشگر

• Carbon cycle in peatland ecosystems
• Stable isotopes of carbon and oxygen
• Method development and validation in environmental analysis
• +۱ مورد دیگر

Patrick Guth is a Researcher in the Ecohydrology and Biogeochemistry Research Group at the Institute of Landscape Ecology, University of Münster. He has held his current Research Associate position since April 2019, following a Research Assistant role from April 2018 to April 2019, focusing on carbon cycling dynamics and stable isotope applications in peatland ecosystems. His educational background includes: Master of Science in Landscape Ecology (2013-2019), University of Münster. Thesis: "Spatial and Temporal δ 13 C Variability in Emitted Methane and its Relationship to Environmental Variables in a Canadian Bog", conducted at Mer Bleue Bog, Ottawa (2018-2019) in collaboration with Carleton University and McGill University. Bachelor of Science in Chemistry (2010-2013), University of Münster. Guth's research integrates fieldwork in peatland ecosystems with laboratory analysis, specializing in carbon cycle processes, stable isotope fractionation, and analytical method development for complex environmental matrices. His work frequently employs UAV technology for data collection and examines redox dynamics in organic soils, contributing to global peatland restoration initiatives. His 2022-2023 publications reveal a dual research trajectory: biogeochemical studies on electron accepting capacities in diverse peat materials (explaining CO 2 /CH 4 formation) and biotechnological applications for waste valorization. These works demonstrate interdisciplinary connections between peatland science, greenhouse gas modeling, and circular economy approaches in environmental technology. He supervises laboratory practical courses in instrumental analytical chemistry for landscape ecologists and teaches biogeochemistry in bachelor's and master's programs. From 2020-2022, he represented academic staff on the Institute of Landscape Ecology's board, contributing to institutional governance while mentoring students in field measurement techniques at research sites like Mer Bleue Bog.

• Human Capital
• Socioeconomic Inequalities
• Educational Decision-Making
• +۳ مورد دیگر

Pia Pinger is Professor at the Department of Economics, University of Cologne, and serves as Speaker of the excellence cluster ECONtribute - Markets & Public Policy . She holds affiliations as IZA Research Fellow and CESifo Affiliate, with research spanning human capital, socioeconomic inequalities, and behavioral economics. Her educational background includes a Ph.D. from the University of Mannheim. Pinger's work employs causal inference methods to examine how early-life conditions shape lifelong outcomes. She investigates educational decision-making through microeconometric analyses, explores socioeconomic disparities in childhood development, and integrates psychological frameworks into economic models. Her studies frequently bridge economics with demography and public health, revealing mechanisms behind intergenerational transmission of inequality. Publication trends indicate sustained focus on intergenerational health/economic effects (2016-2024), behavioral foundations of economic preferences (2017-2020), and labor market dynamics (2024). Recent work combines experimental designs with large-scale datasets to isolate causal relationships in wage negotiation and childhood development. Her scientific recognition includes: IZA Research Fellow Pinger leads project A02 within the ECONtribute cluster and mentors junior researchers through collaborative projects. Her secured funding supports investigations into human capital formation and policy interventions. Current work-in-progress examines parental investment patterns and talent attraction mechanisms. She directs research activities within the ECONtribute excellence cluster, coordinating interdisciplinary teams studying market behavior and public policy design. Her project leadership (A02) focuses on socioeconomic determinants of human capital development.

• Geophysics
• Marine Geology
• Seismology
• +۳ مورد دیگر

Erik Fredrickson is a Research Fellow at the Institute for Geophysics within the Jackson School of Geosciences at The University of Texas at Austin. His work focuses on seafloor geodesy, with expertise in subduction zone dynamics, slow slip events, and tectonic deformation monitoring. He is affiliated with the Institute for Geophysics and uses advanced instrumentation like tilt accelerometers and pressure gauges. His research emphasizes calibrating seafloor instruments to distinguish tectonic signals from oceanographic noise, particularly in critical zones like Cascadia, Hikurangi, and Alaska margins. Recent studies include analyzing decade-long geodetic datasets to understand near-trench megathrust slip behavior and optimizing sensor configurations for detecting slow-slip earthquakes. Key contributions include developing self-calibrating tilt measurement methods and advancing circulation-informed geodetic techniques to better characterize plate boundary processes. His work bridges geophysics, oceanography, and tectonics to improve hazard assessment and monitoring strategies. Erik’s research has been applied to both subduction zone studies (e.g., Hikurangi, Cascadia) and volcanic systems like Axial Seamount. He collaborates extensively on field campaigns deploying seafloor instruments and refining data analysis frameworks to isolate tectonic deformation signals.

David J. Loveمشاهده پروفایل

استاد

• Communication theory
• Information theory
• MIMO wireless systems
• +۶ مورد دیگر

David J. Love is the Nick Trbovich Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. He leads the Purdue NextG Center for Communications and Sensing (XGC) and holds Fellowships from IEEE, AAAS, and NAI. His research focuses on 6G systems, MIMO communications, millimeter-wave and terahertz technologies, and security in wireless networks. He has authored over 150 papers and holds 32 patents, with notable contributions to codebook-based precoding used in 4G/5G standards. Education: B.S. (Highest Honors), M.S.E., and Ph.D. in Electrical Engineering from The University of Texas at Austin (2000–2004). Research Interests: Communication theory, feedback systems, massive MIMO, integrated sensing and communications (ISAC), and wireless security. His work bridges theoretical advancements with practical implementations in 5G/6G systems. Publications Trends: Recent work emphasizes federated learning for edge networks, 6G architecture, and secure wireless systems. Key themes include privacy-preserving machine learning, hybrid satellite-terrestrial networks, and waveform design for ISAC. Awards: Includes the IEEE Communications Society Bennett Prize (2024), NAI Fellow (2023), AAAS Fellow (2022), and multiple best paper awards. Recognized as a Thomson Reuters Highly Cited Researcher (2014–2015). Advising & Grants: Advised over 30 Ph.D. students. Current leadership roles include Director of the NextG Center and Co-Lead of NSF IoT4Ag. Active in grants related to IoT, precision agriculture, and spectrum intelligence. Labs/Teams: Leads the NextG Center, involved in NSF Engineering Research Centers (ERCs), and collaborates with industry on applied wireless research.

Michael Pollmannمشاهده پروفایل

استادیار

• Econometrics
• Causal Inference
• Machine Learning
• +۳ مورد دیگر

Michael Pollmann is an Assistant Professor of Economics at Duke University’s Trinity College of Arts & Sciences. His research focuses on econometrics, causal inference, and machine learning, with a particular emphasis on spatial data analysis and healthcare economics. He holds a PhD from Stanford University (2022), where he also earned an MA (2020) and served as a teaching assistant and instructor for econometrics and math courses. Education: PhD in Economics, Stanford University, 2022 MA in Economics, Stanford University, 2020 MSc in Econometrics & Operations Research, Maastricht University, 2015 BSc in Econometrics & Operations Research, Maastricht University, 2014 Research Interests: Pollmann develops novel econometric methods for causal inference, including semi-parametric approaches for randomized experiments and spatial treatment analysis. His work bridges traditional econometric techniques with modern machine learning tools, addressing challenges in healthcare policy, treatment effect estimation, and policy evaluation. Awards: Recipient of the B. F. Haley and E. S. Shaw Fellowship (2021–22) Outstanding Teaching Assistant Award (Stanford, 2018 & 2019) Participant in the Lindau Nobel Laureate Meeting on Economic Sciences (2022) Teaching & Service: At Duke, he teaches advanced econometrics and causal data analysis courses. He co-organizes the Gary Chamberlain Online Seminar in Economics and actively participates in PhD admissions and junior faculty recruitment. His professional activities include refereeing for top journals like the American Economic Review and Econometrica . Labs/Teams: Collaborates with institutions such as LMU Munich, University of Bonn, and University of Mannheim, focusing on interdisciplinary research in econometrics and applied economics.

Suzanne Aigrainمشاهده پروفایل

استاد

• Exoplanets
• Stellar Activity
• Data Analysis
• +۴ مورد دیگر

Prof Suzanne Aigrain is a Professor of Astrophysics at the University of Oxford and a Fellow of All Souls College. Previously, she was a Lecturer at the University of Exeter and a PPARC Postdoctoral Fellow at the Institute of Astronomy in Cambridge. Her research focuses on exoplanet detection and characterization using transit and radial velocity methods, stellar activity impacts on exoplanet studies, and Bayesian data analysis. She leads the PLATO mission's data analysis efforts and is a key member of the Terra Hunting Experiment (THE), which will use the HARPS3 spectrograph to search for nearby Earth-like planets. Her work includes pioneering Gaussian Process regression techniques to analyze exoplanet datasets and mitigate stellar activity effects. She is Principal Investigator of the European Research Council-funded 'GPRV' project and receives UKRI/STFC funding for TESS and PLATO missions. Research interests include exoplanets, stellar activity, and advanced data analysis methods. She has contributed to space missions like CoRoT, Kepler, K2, TESS, and PLATO (launching 2026). Her recent work emphasizes developing algorithms to handle activity noise in RV data and simulating PLATO mission outcomes. She also promotes citizen science and best practices in data analysis. Key collaborations include the Stars & Planets @ Oxford research group and involvement with the Terra Hunting Experiment. Her research has advanced methods for detecting small planets and characterizing their properties using high-precision photometry and spectroscopy.

Michel Tsamadosمشاهده پروفایل

دانشیار

• Climate Sciences
• Polar Observation
• Sea Ice Dynamics
• +۳ مورد دیگر

Dr. Michel Tsamados is an Associate Professor in Polar Observation & Modelling at the Department of Earth Sciences, University College London (UCL). He specializes in integrating remote sensing and numerical modeling to study polar climate systems, with a focus on sea ice dynamics, snow cover, and ocean-atmosphere interactions. His work bridges fundamental material science principles with applied climate research, leveraging satellite data (e.g., CryoSat-2, ICESat-2) and advanced machine learning techniques to improve model parameterizations and observational products. Key affiliations include UCL's Centre for Polar Observation and Modelling (CPOM) and collaborations with the Alan Turing Institute and Met Office Academic Partnership (MOAP). His research explores AI applications in polar climate analysis, geoengineering feasibility studies, and historical climatic data recovery (e.g., Ottoman-era rainfall records). Research interests encompass sea ice thickness estimation, snow depth retrieval via dual-frequency radar, and understanding drivers of Arctic amplification. He teaches courses on ocean physics, climate change, and climate principles. Current projects include advancing Southern Ocean tide models (ALBATROSS), optimizing sea ice thickness algorithms, and analyzing extreme cyclone impacts on sea ice. His contributions include developing satellite-derived products like the first summer Arctic sea ice thickness record and pan-Arctic drag coefficient datasets. He actively participates in multidisciplinary initiatives like the MOSAiC Distributed Network and CRISTAL mission preparations.

Seonkyoo Yoonمشاهده پروفایل

استادیار

• Hydrogeology
• Flow in Porous Media
• Reactive Transport
• +۵ مورد دیگر

Dr. Seonkyoo Yoon is an Assistant Professor in the Department of Geological Sciences at the University of Florida. His research focuses on physical hydrology, integrating theoretical, computational, experimental, and field methods to study water flow and reactive transport in porous and fractured geological media. Key areas include Karst water systems, acid rock fracturing, and natural hydrogen dynamics across micro-to-field scales. Education: Ph.D. in Hydrology from Massachusetts Institute of Technology (2016). Research Interests: Hydrogeology and Flow in Porous Media Reactive Transport and Fluid-Rock Interaction Inverse Problems in Subsurface Systems Fractured Aquifer Dynamics Contaminant Fate and Transport Publications highlight advancements in fracture network modeling, variable-density flows, and DNAPL migration prediction. His work bridges computational innovation with practical environmental challenges in subsurface systems. Labs/Teams: Active in the University of Florida's geological sciences laboratories, focusing on numerical modeling and field experiments for subsurface flow characterization.

Florian Gunsiliusمشاهده پروفایل

دانشیار

• Nonparametric Econometrics
• Optimal Transport Theory
• Causal Inference
• +۳ مورد دیگر

Florian Gunsilius is an Associate Professor in the Department of Economics at Emory University. His research focuses on nonparametric econometric methods, optimal transport theory, and causal inference. He earned a PhD in Economics from Brown University (2019), an MA in Economics (2014), and a BSc/MPE in Economics from the Frankfurt School of Finance and Management (2012). His work bridges theoretical econometrics and applied policy analysis, particularly in areas requiring innovative statistical techniques. Dr. Gunsilius's research interests include statistical identification, estimation of causal effects, and applications of optimal transport to economics. He has developed methods for analyzing treatment effects, demand systems, and policy impacts using advanced mathematical frameworks like free discontinuity regression and Wasserstein projections. His recent publications (2021–2025) emphasize causal inference in observational data, synthetic control methods, and nonlinear econometric modeling. Notable contributions include distributional synthetic controls for policy evaluation and free discontinuity regression for structural estimation. He maintains an active research agenda in nonparametric approaches to economic modeling.